The present invention relates to product checkout devices and more specifically to a produce texture data collecting apparatus and method.
Bar code readers are well known for their usefulness in retail checkout and inventory control. Bar code readers are capable of identifying and recording most items during a typical transaction since most items are labeled with bar codes.
Items which are typically not identified and recorded by a bar code reader are produce items, since produce items are typically not labeled with bar codes. Bar code readers may include a scale for weighing produce items to assist in determining the price of such items. But identification of produce items is still a task for the checkout operator, who must identify a produce item and then manually enter an item identification code. Operator identification methods are slow and inefficient because they typically involve a visual comparison of a produce item with pictures of produce items, or a lookup of text in table. Operator identification methods are also prone to error, on the order of fifteen percent.
A produce data collector disclosed in the co-pending application includes a spectrometer. The spectrometer preferably includes a linear variable filter (LVF) and a linear diode array (LDA), which capture spectral information about a produce item.
Additional information is highly desirable for improving the accuracy of recognition and classification of a number of items. One such type of information is texture information.
There are two kinds of texture information that are relevant to identification, spatial texture and color texture. Spatial texture includes surface roughness caused by small-scale ridges and valleys, peaks and dips, leaflets, etc. Spatial texture also includes the apparent texture of a collection of items. For example, spatial texture includes the collective surface roughness of a bag of beans or a bunch of green onions.
Color texture includes small-scale color variation over the surface of the item. For example, color texture includes color stripes and spots over the surface of an apple. Color texture also includes brightness variation.
Therefore, it would be desirable to provide a produce texture data collecting apparatus and method which is able to collect texture information in order to assist in determining the identity of a produce item.
In accordance with the teachings of the present invention, to a produce texture data collecting apparatus and method is provided.
The apparatus includes a first light for illuminating a produce item from a first direction during a first time, a second light for illuminating the produce item from a second direction different from the first direction during a second time different from the first time, and an image capture device for capturing a first image of the produce item during the first time and a second image during the second time.
The light reflected from the produce item may also be directed through a spectrometer to obtain spectral data to assist with recognition.
A method of collecting texture data associated with a produce item includes the steps of illuminating the produce item with first and second lights from different directions during different times, capturing a first and second images of the produce item during the different times while the produce item is being illuminated by the first and second lights, and determining texture information from the first and second images of the produce item.
It is accordingly an object of the present invention to provide a produce texture data collecting apparatus and method.
It is another object of the present invention to provide a produce texture data collecting apparatus and method which supplement spectral data collection.